Research on Five-Phase Flux-Intensifying Permanent Magnet Motor Drive System Based on New Active Sensorless Strategy

For the sensorless control system of the five-phase interior permanent magnet (IPM) motors, its saturation effect greatly affects the estimated accuracy of rotor position, which will not meet the requirement of multi-operating conditions for electric vehicles (EVs). To solve the saturation effect problem, a new active sensorless control strategy is proposed from the perspective of the motor drive system. Based on the analysis of the influence of the saturation effect on the rotor position observation, a five-phase flux-intensifying fault-tolerant IPM (FIFT-IPM) motor is proposed with the enhanced reverse saliency effect. Thus, the cross-coupling and parameter variation caused by the saturation effect can be suppressed. Furthermore, from the perspective of the control algorithm, a secondary harmonic suppression method based on adaptive-band filtering (ABF) is proposed to further improve the dynamic and steady-state performance of the five-phase FIFT-IPM motor drive system without position sensor control. Finally, the correctness and effectiveness of the proposed strategy are verified by experimental results.

Abstract-For the sensorless control system of the five-phase interior permanent magnet (IPM) motors, its saturation effect greatly affects the estimated accuracy of rotor position, which will not meet the requirement of multi-operating conditions for electric vehicles (EVs).To solve the saturation effect problem, a new active sensorless control strategy is proposed from the perspective of the motor drive system.Based on the analysis of the influence of the saturation effect on the rotor position observation, a five-phase flux-intensifying fault-tolerant IPM (FIFT-IPM) motor is proposed with the enhanced reverse saliency effect.Thus, the cross-coupling and parameter variation caused by the saturation effect can be suppressed.Furthermore, from the perspective of the control algorithm, a secondary harmonic suppression method based on adaptive-band filtering (ABF) is proposed to further improve the dynamic and steady-state performance of the five-phase FIFT-IPM motor drive system without position sensor control.Finally, the correctness and effectiveness of the proposed strategy are verified by experimental results.

I. INTRODUCTION
A S ENVIRONMENTAL protection and energy security have widely concerned various countries in the world, electric vehicles (EVs) have been widely concerned with their high efficiency and low pollution [1], [2].EVs need to face frequent start-stop, heavy-duty climbing, high-speed cruising, and other operating conditions.Five-phase interior permanent magnet (IPM) motor has the advantages of strong fault tolerance, high efficiency, high power density, and good weak magnetism, etc., which provides an ideal choice for EVs traction motor [3], [4], [5].
For the five-phase IPM motor drive system, it is necessary to use mechanical position sensors, such as photoelectric encoder and rotation, usually needed to be used to obtain the rotor position information for high-performance control; however, the use of mechanical position sensors not only increases the volume and cost of the system but also reduces its reliability.The sensorless control technology can effectively overcome the above-mentioned problems, which has become one of the key research directions in the field of motor control [6], [7], [8].According to the applicable range of speed, sensorless control techniques are mainly divided into two types: the observer estimation method suitable for medium-/high-speed operation and the saliency tracking method suitable for zero-/low-speed operation [9], [10], [11].For the motor sensorless drive system under zero/low speed, its performance is limited by the motor's saturation effect, which mainly includes three aspects: parameter variation, cross-coupling effects, and secondary saliency caused by saturation [12], [13].At present, the algorithm of the five-phase IPM motor sensorless controller is often directly borrowed from the corresponding one in three-phase motors [14].Therefore, the sensorless control of the fivephase IPM motor also inherits the shortcomings and problems existing in the sensorless control technology of three-phase motors.In addition, due to EV applications with multiple operating conditions, the algorithm difficulty of sensorless control for the five-phase IPM motor will be further increased.
Because of the saturation effect of the conventional fivephase IPM motor, its parameters under different operating conditions vary greatly, which will seriously affect the estimated accuracy of the rotor position and the operating range of sensorless control [15], [16].The parameter identification method is the most direct solution to variable parameters.With the adoption of this method on the position observer, the estimated accuracy of the rotor position can be improved theoretically [17].Furthermore, aiming at this problem that the cross-coupling effect of the conventional fivephase IPM motor seriously reduces the stability of sensorless control system, Wang et al. [18] proposed a rotor position offset method.With the change of the current vector angle, the estimated position offset can be identified and compensated online, which could effectively reduce the error of position estimation.In general, from the perspective of the control algorithm optimization, the influence of parameter variation and cross-coupling effect on the estimated accuracy of rotor position can be suppressed to a certain extent.The existing sensorless control methods for the above problems often require the use of a large number of decoupling algorithms, which, however, increases the hardware requirements of the drive system and cannot adapt to the condition with rapid load change.
To overcome the above problems, Wu et al. [19] proposed a flux-intensifying IPM motor.In the motor design stage, the influence of parameter variation and cross-coupling effect on the estimated accuracy of rotor position was considered in advance.By improving the rotor structure, the fluxintensifying IPM motor has the characteristics of reverse saliency and very little motor parameter change, which can improve the motor's sensorless operation performance.Based on this design concept, a five-phase flux-intensifying interiorpermanent-magnet (FI-IPM) motor with the flux-intensifying effect was proposed in [20], which could achieve strong fault tolerance and excellent sensorless operating capacity.Nevertheless, due to a large number of rotor poles, the space for setting the q-axis magnetic barrier of the rotor is limited.In addition, due to the use of concentrated winding of the five-phase FI-IPM motor, its reverse saliency ratio is relatively low, which is difficult to meet the requirements of multiple operating conditions of the motor sensorless drive system for EVs.
On the other hand, the secondary saliency caused by saturation will cause a large number of harmonics in the observed current, which leads to the harmonic distortion of the rotor position estimation [21].Typically, the secondary saliency is determined by the stator space structure of the motor itself.So, it is difficult to reduce the influence of secondary saliency by optimizing the motor structure [22].Then, such effect of the secondary saliency was considered to be suppressed from the perspective of motor control.Diaz Reigosa et al. [23] adaptively decoupled the secondary saliency by constructing a structured neural network, which decreased the influence of the secondary saliency on position observation.Nevertheless, the high complexity of the neural network algorithm extremely increases the hardware burden.In [19], the secondary saliency harmonics under different loads were measured offline, and a real-time harmonic lookup table was established for real-time decoupling.The offline measurement method, however, requires a lot of preliminary work, and the spatial gradient of the secondary saliency is relatively complex, which brings a great challenge to accurate decoupling under the condition of rapid load change [24].
In summary, aiming at the problem of the increased estimated error of rotor position caused by the motor saturation effect, existing research was usually carried out passively from the two perspectives of improving the control algorithm or optimizing the motor structure, which is difficult to guarantee the excellent estimated accuracy of rotor position under multiple operating conditions.Therefore, based on the analysis of the saturation effect on position observation, a new active sensorless strategy from the perspective of the motor drive system is proposed in this article.The main contributions of this research are as follows.
1) In the motor structure design stage, a five-phase fluxintensifying fault-tolerant IPM (FIFT-IPM) motor with the enhanced reverse saliency effect is proposed to suppress the impact of cross-coupling and parameter variation on the estimated accuracy.2) From the perspective of the control algorithm, adaptive linear neuron filter (ADALINEF) and adaptive band filtering (ABF) are introduced to improve the sensorless dynamic response performance of the five-phase FIFT-IPM motor while suppressing the secondary saliency harmonics.3) This article first attempts to propose a simplified active sensorless strategy from the perspective of the five-phase FIFT-IPM motor drive system to achieve both good motor sensorless operating performance and sensorless control performance.The rest of this article is arranged as follows.In Section II, according to the conventional sensorless control algorithm, the influence of the saturation effect on rotor position estimation will be analyzed.Then, a new active sensorless strategy will be presented in Section III.In Section IV, the experimental results will be given to validate the proposed new active sensorless strategy.Finally, key conclusions will be drawn in Section V.

II. TRADITIONAL SENSORLESS CONTROL OF FIVE-PHASE PERMANENT MAGNET MOTOR A. Mathematical Model of the Five-Phase IPM Motor
The vector control of the five-phase IPM motor can be divided into fundamental space and third harmonic space.Based on [1], the stator voltage equation can be expressed as where u d1 , u q1 , i d1 , i q1 , L d1 , and L q1 are the stator voltage, current, and inductance in the fundamental space, respectively.u d3 , u q3 , i d3 , i q3 , L d3 , and L q3 are the stator voltage, current, and inductance in the third harmonic space, respectively.R s is the stator resistance; ω e is the electric angular velocity; ψ 1 and ψ 3 are the fundamental flux and third harmonic flux, respectively.Also, the electromagnetic torque T e can be expressed as where P n is the pole pairs.
Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.At present, pulsating high-frequency (HF) signal injection method has the advantages of simple implementation, high tracking accuracy, and little influence by parameter changes, which is the most commonly used position observation method under zero/low speed [25].The block diagram of a sensorless control system of the five-phase IPM motor based on the pulse HF injection method is shown in Fig. 1, where the signal demodulation process includes a phase detector (PD), a loop filter (LF), and a voltage-controlled oscillator (VCO).Noted that ASR represents the automatic speed regulator, and ACR is the automatic current regulator.The HF mathematical model of the five-phase permanent magnet synchronous motor (PMSM) in fundamental wave space can be simplified as The HF voltage signal injected into the d 1 q 1 axis is where U h and ω h are the amplitude and frequency of the injected HF voltage signal, respectively.Defining the actual position as θ e , the estimated position as θe , the estimated rotor position error as θe .According to the coordinate transformation [20], the HF response current in the d 1 q 1 -axis can be estimated as where is the differential inductance.According to (5), the estimated HF response current in the q 1 -axis includes the term of estimated rotor position error.As shown in Fig. 1, after demodulation of the estimated HF response current in the q 1 -axis, the estimated rotor position error function can be obtained as where According to (6), when the position error θe is small enough, f ( θe ) is approximately proportional to θe .By adjusting f ( θe ) to 0 through the PLL, the estimated rotor position and speed can be obtained.

C. Problem Analysis
1) Effect of Cross-Coupling: Because of the cross-coupling effect, when the HF injection method is adopted, the rotor position is estimated with offset error [26], which can be expressed as According to (7), the existence of cross-coupling mutual inductance will lead to a phase shift in rotor position estimation.It is worth noting that the motor's cross-coupling mutual inductance will increase as the increased load.When the motor operates under heavy-duty climbing conditions or frequent start-stop conditions, the estimated accuracy of the rotor position will be seriously limited by its cross-coupling effect.
2) Effect of Parameter Variation: The îq1h used to extract position signal f ( θe ) is mainly determined by the fundamental injected HF voltage signal.After Fourier analysis of the injected HF signal, ûd1h can be approximated as follows: For ûq1h , its fundamental component ûq1h1 is where ρ 1 = E p q1 ( θe )a η1 and ρ 2 = E p q1 ( θe )b η1 , ρ 1 and ρ 2 are determined by the dc bus voltage E and the switch functions of each bridge arm of the inverter a η1 and a η1 .Combined with ( 6), (8), and ( 9), the rotor position error function can be obtained as follows: When the estimated rotor position error function approaches 0, the expression of the estimated rotor position error can be obtained as follows: where λ = L q1 /L d1 is the salient rate of the motor.According to (11), when the protrusion rate of the motor is greater than or less than 1, the estimated accuracy of the rotor position is higher.When the protrusion rate of the motor approaches 1, the estimated error will increase accordingly.Therefore, to achieve the high-precision rotor position estimation of the sensorless control, it is necessary to ensure that the salient ratio (L q1 /L d1 ) of the driving motor under different operating conditions is stable and much higher than 1.Fig. 2 shows the salient ratio of the traditional five-phase IPM motor under different loads.
Because of the smaller reluctance torque, the current trajectory is closer to the q 1 -axis under MTPA operation.From Fig. 2, it can be found that for the traditional five-phase IPM motor, the salient ratio crosses four contour lines when the current increases from 0 to the rated value.Correspondingly, the salient ratio changes by 0.147.In addition, the saliency effect even disappears during the change.From (11), it can be known that the salient ratio has a great influence on the estimated rotor position error.When the saliency effect disappears, the estimated rotor position error will increase infinitely.Also, the estimation algorithm will fail to obtain the rotor position.Therefore, the sensorless operating capability of the traditional five-phase IPM motor is poor.
3) Effect of Secondary Saliency: Because of the secondary saliency in the five-phase IPM motor, its HF carrier current signal contains the secondary harmonic component, which will cause the estimated rotor position fluctuation and affect the operating performance of the sensorless control system.Fig. 3 shows the Fourier analysis results of the position estimation error of the traditional five-phase IPM motor at a speed of 100 r/min with the HF pulse injection method.It can be seen that the estimated rotor position error contains multiple harmonic components related to the motor speed, where twotimes frequency and three-times frequency of the harmonics are the higher content.
When considering the secondary saliency of the motor [23], the estimation of the HF response current in the q 1 -axis under the fundamental shafting system should be rewritten as where i and j are the number of secondary, i = 1 is the primary saliency, and the others are the secondary saliency.After signal modulation of the estimated HF response current in the q 1 -axis, a new rotor position error function can be obtained as According to (13), the rotor position error function contains a large number of low-order secondary harmonic components.Also, the secondary harmonic frequency is an integral multiple of the electrical frequency of the motor.Therefore, the frequency of the harmonic in the rotor position error caused by secondary saliency is an integral multiple of the motor frequency.The harmonic content at nonintegral times of motor frequency is low.The secondary saliency will reduce the signal-to-noise ratio (SNR) of the main saliency component of the rotor position error function and cause multiharmonic oscillation in estimating the rotor position.Thus, it is necessary to suppress the secondary salient harmonics to reduce the influence of secondary salient on sensorless control.
For the five-phase IPM motor under multiple operating conditions, its sensorless control performance suffers a more serious saturation effect.Thus, it is necessary to propose a sensorless strategy for suppressing the saturation effect to maintain superior dynamic and static performance and a wide speed range of the five-phase IPM motor sensorless drive system for complex and variable operations.

III. NEW ACTIVE SENSORLESS STRATEGY
From the above analysis, it can be known that the motor saturation effect has a great influence on the observation accuracy of the rotor position and reduces the operating performance of the sensorless drive system.In existing studies, suppression schemes for parameter variation [10], crosscoupling [12], or secondary saliency [16] can, however, only solve part of the problems caused by the saturation effect.Hence, from the perspective of the motor drive system, a new active sensorless strategy to suppress the saturation effect is proposed in this article, which can improve the sensorless operating performance of the five-phase IPM motor under multiple operating conditions.

A. Structure Design of the Five-Phase FIFT-IPM Motor
Because of the saturation effect, the traditional five-phase IPM motor is difficult to meet the requirements of sensorless control under multiple operating conditions.To overcome the influence of motor cross-coupling effect and parameter variation on the observation accuracy of sensorless control, this article proposes a new five-phase FIFT-IPM motor with the enhanced reverse saliency effect based on satisfying the basic performance of motor torque, efficiency, and fault tolerance, which is more suitable for sensorless control under multiple operating conditions.   in Fig. 5.To realize the motor's reverse saliency feature, it is generally necessary to increase the q-axis magnetic barrier.But for the five-phase FI-IPM motor, a 20/18 slot pole combination is usually adopted.Because of the large number of poles, the space for setting the q-axis magnetic barrier on the rotor is limited.At the same time, the use of concentrated windings makes the d-q-axis coupling phenomenon obvious, which is not conducive to obtaining obvious reverse salient characteristics of this kind of motor.To ensure fault tolerance and achieve the obvious reverse salient characteristics, a 10/8 slot pole combination is selected in this article.
From Fig. 4, it can be known that a large q-axis magnetic barrier is set to further improve the reverse salient ratio of the motor.Also, the q-axis magnetic barrier adopts a concave arc, which can reduce the saturation of the d-axis magnetic circuit and thus reduce iron consumption.The thin and long rectangular of the permanent magnet is adopted, and it is located close to the rotating axis, which can improve the d-axis inductance and reduce the demagnetization risk of the permanent magnet.Furthermore, the planar stator tooth tip is used to reduce the cross saturation of magnetic circuits, which is effective in further improving the motor's reverse salient ratio.
The five-phase FIFT-IPM motor adopts single-layer concentrated winding to realize phase-phase isolation, which has strong fault-tolerant performance.In addition, the reverse saliency effect can relieve the cross-saturation effect.The q-axis magnetic barrier can reduce the sensitivity of L q to qaxis current changes.Then, the degree of motor parameters changing with load can be reduced, which can effectively improve the dynamic and steady-state sensorless operating Fig. 6.Salient ratio map of the five-phase FIFT-IPM motor.

TABLE I PARAMETERS OF FIVE-PHASE FIFT-IPM MOTOR
performance.The planar stator tooth top design can adjust the air-gap reluctance to obtain more sinusoidal back EMF and lower torque ripple.At the same time, the FIFT-IPM motor has enhanced reverse salient characteristics.Hence, the FIFT-IPM motor possesses a wider current angle when the current control and the i d amplitude are smaller under the flux-weakening control, which can effectively minimize the risk of permanent magnet demagnetization.Owing to the sinusoidal back EMF and strong anti-demagnetization capacity, the stability of the FIFT-IPM motor under medium-/high-speed conditions can be improved.Also, its back EMF-based sensorless control performance under medium/high speed can be ensured.
Table I lists the main parameters of the five-phase FIFT-IPM motor.Fig. 6 shows the salient ratio of the five-phase FIFT-IPM motor under different load currents.Compared with Fig. 2, it can be known that different from the traditional five-phase IPM motor, the salient ratio of the proposed fivephase FIFT-IPM motor varies little with the load current and only crosses two contour lines.The salient ratio variation is only 0.094, which decreases by about 63.9%.Also, the salient ratio is always less than 1.Therefore, the fivephase FIFT-IPM motor has better saliency characteristics and dynamic sensorless operating capacity.In addition, Fig. 7 shows the comparison of the rotor position absolute error angle waveforms of both motors.It can be found that the error angle of the traditional five-phase IPM motor will be greatly affected by the load current.On the contrary, due to the high magnetic reluctance of the q-axis magnetic circuit of the fivephase FIFT-IPM motor, there is a low saturation degree of the magnetic circuit with the changed load current.Hence, the q-axis inductance will not change greatly, and the error angle is always kept at a small value.The above analysis verifies that the five-phase FIFT-IPM motor can effectively improve sensorless operating performance.From the above analysis in Section II-C, it can be known that the sensorless control performance under multiple operating conditions can be effectively improved by enhancing the reverse salient effect of the five-phase IPM motor.Since the characteristics of the secondary saliencies are determined by the spatial structure of the motor, the five-phase FIFT-IPM motor, however, still has the problem of secondary saliency.Then, the high-precision sensorless operating performance of the five-phase FIFT-IPM motor drive system is still needed to be exploited.To further suppress the harmonics caused by the secondary saliency of the five-phase FIFT-IPM motor for comprehensively improving the observation accuracy of the rotor position, the improved sensorless control algorithm is proposed in this article.

B. Secondary Harmonic Suppression Strategy Based on
Adaptive-Band 1) Adaptive Suppression of Secondary Harmonic: To suppress the effect of secondary saliency harmonics on rotor position observation, an ADALINEF based on the recursive least square (RLS) method is proposed.The filter coefficients are adjusted by the adaptive algorithm to suppress the specific subharmonics in the position error signal.Fig. 8 presents the schematic of ADALINEF based on RLS.ADALINEF can filter the specific subharmonics in f k ( θe ) online.Since each branch of harmonic component filtering has the same structure and characteristics, taking the +2ω e subharmonics with the highest content as an example, the detailed filtering principle diagram is given.The input signal U (n) of ADALINEF is the rotor position error function f k ( θe ) modulated by the HF injection method.Also, the sine and cosine function of the rotor position θe estimated by a specific multiple is used as the reference signal of the ADALINEF harmonic input signal.The adjustable weight component x(k) of ADALINEF is updated online in real-time by an adaptive algorithm, which can make the harmonic estimate converge to its actual value.After processing the harmonic reference signal r (n) and the adjustable weight component x(k), the desired output signal y(n) of the filter is obtained.In addition, the desired fundamental signal Y (n) can be obtained with the difference between the input signal u(n) and the desired output signal y(n) of the filter.
Based on the RLS method, the following expression can be obtained as where r 11 (n) = sin(2 θe ) and r 21 (n) = cos(2 θe ) are the harmonic reference signals, and the adjustable filter coefficients x 11 (n) and x 21 (n) are updated online based on harmonic reference signals, which are expressed as where µ is the forgetting factor and 0 < µ < In practice, the initial values of the adjustable filter coefficient x 11 (n) and x 21 (n), the scale H 11 (n) and H 21 (n) of the autocorrelation matrix are selected as follows: The choice of µ and σ directly affects the harmonic suppression effect of ADALINEF.In this article, σ is set as 0.0005, which is used to make the system under an overdamped state to reduce the influence of overshoot.Comprehensively considering the tracking capacity and the stability of the RLS algorithm, the forgetting factor µ is generally chosen to be close to 1, and µ = 0.9995 is chosen in this article.
2) Position Error Signal Extraction Based on ABF: ADALINEF can effectively suppress the position observation error caused by secondary saliency.Yet, the traditional rotor position observation algorithm still suffers from the problem of poor dynamic response.To further improve the dynamic response performance of sensorless control, an ABF based on the all-pass network is introduced to extract rotor position error signals instead of the fixed bandwidth filter.All-pass network filter has constant amplitude-frequency characteristics and HF where , ω m is the filtering bandwidth with 3 dB attenuation; p = cos(ω n T s ), ω n is the resonant frequency point.The structure of the ABF is shown in Fig. 9, where U (s) and Y (s) are the input and output signals of the all-pass network.It can be found that the structure of the ABF is simple, and the parameters are easy to be adjusted.In the ABF, the resonant frequency is set as where ω c is the frequency of the injected HF signal, ωr is the estimated speed of the motor, and the resonant frequency is automatically adjusted with the motor speed to reduce the phase delay brought by the filter.Setting the filtering bandwidth as where ω b is the adjustable bandwidth, λ is the dynamic regulating factor.When the motor runs stably, the dynamic regulating factor does not work.At this time, the filter bandwidth depends on ω b .When the motor runs at variable speed, the dynamic regulating factor is activated.And the filtering bandwidth is adaptively adjusted according to the error between the actual speed and the given speed.Thus, the dynamic response performance of the position-free control can be improved.In order to ensure the filtering effect in the process of dynamic adjustment and avoid excessive bandwidth, the dynamic regulating factor was set as 10 in this article.
According to (6), the modulated current can be expressed as where HF(2ωt) = Î q1h cos(2ω h t).From ( 22), it can be found that the modulated current contains two-order HF injected harmonics.Then, ω c in ABNF is set as 2ω h to obtain the position error signal f k ( θe ).

C. Improved Sensorless Drive System
The control scheme of the proposed active sensorless strategy for the five-phase FIFT-IPM motor is shown in Fig. 10.An active sensorless strategy is proposed to improve the observation performance from the perspective of motor design and motor control.In the aspect of motor design, the five-phase FIFT-IPM motor with the enhanced reverse saliency effect is proposed, which can suppress the influence of the motor saturation effect on the estimated accuracy of rotor position at zero/low speed.Also, the antidemagnetization and flux-weakening capacity is enhanced, which can improve the stability of high-speed sensorless operation to a certain extent.On the other hand, a sensorless control strategy of secondary harmonic suppression based on an adaptive band is proposed to further overcome the influence of secondary saliency on the observed accuracy of rotor position.With the proposed sensorless control scheme, the secondary harmonics of the five-phase FIFT-IPM motor can effectively be filtered, and the stability of rotor position observation can be improved.Furthermore, with the adaptation band algorithm, the center frequency and bandwidth of the filter can adaptively change with the motor speed.Therefore, the dynamic performance of the sensorless drive system can be improved.

IV. EXPERIMENTAL VERIFICATION
To validate the effectiveness of the proposed new active sensorless control strategy, an experimental platform of the five-phase FIFT-IPM motor sensorless control system based on dSPACE1007 is built, as shown in Fig. 11.The Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.

A. Comparison and Verification of Motor Performance
Figs. 12 and 13 show the sensorless steady-state waveforms of the traditional five-phase IPM motor and the five-phase FI-IPM motor with weak saliency at 100 r/min.From Fig. 12, it can be seen that for the traditional five-phase IPM motor, its average value of the position error is −0.09 rad, its peakto-peak value of the position error is 0.22 rad, and its peak-topeak value of the speed error is 38.2 r/min.For the five-phase FI-IPM motor with weak saliency, as shown in Fig. 13, its average position error is −0.05 rad, its peak-to-peak value of the position error is 0.27 rad, and its peak-to-peak value of the speed error is 42.1 r/min.In addition, the rotor position errors of both motors have high secondary salient harmonics.Therefore, it can be obtained that both motors have poor stability of sensorless operation and cannot meet the highperformance sensorless operating requirements of EVs.
Fig. 14 shows the comparison of the estimated rotor position errors of the traditional five-phase IPM motor and the proposed five-phase motor varying with the load.It can

14.
Error angles of the five-phase IPM motor and the five-phase FIFT-IPM motor.
be seen that the position error of the traditional five-phase IPM motor reaches about 30 • at a load of 6 N•m, which demonstrates that its position error varies greatly with the increased load.By contrast, the position error of the fivephase FIFT-IPM motor is less affected by the load change.The position error of the five-phase FIFT-IPM motor is only about 10 • at the load of 6 N•m, verifying that the proposed five-phase FIFT-IPM motor has superior antisaturation ability and excellent sensorless operation performance.Fig. 15 shows the comparison diagram of the position error of the proposed five-phase FIFT-IPM motor and the five-phase FI-IPM motor in steady-state.It can be seen that the average position error of the five-phase FI-IPM motor is −0.05 rad, while the average position error of the proposed five-phase FIFT-IPM motor is close to 0. Under the same load, the proposed five-phase FIFT-IPM motor has higher position estimation accuracy.The sensorless operation performance of the proposed five-phase FIFT-IPM motor is verified.

B. Stability Performance
Fig. 16 shows the comparison of the steady-state performance of the five-phase FIFT-IPM motor with the traditional method, the adaptive notch method [7], and the proposed ABF method.It can be observed that compared with the traditional method and the adaptive notch method, the speed estimation error of the proposed method in this article is reduced by 35.4% and 18.8%, respectively.Also, the estimated rotor position errors are reduced by 44% and 20%, respectively.Hence, it can be obtained that the proposed ABF algorithm in this article can effectively suppress the observation errors of speed and rotor position caused by the secondary saliency of the motor.In addition, due to the influence of the inverter nonlinearity and sensor detection error, some steadystate error of the proposed method still exists.
The Fourier analysis of the position estimation error of the above three methods is shown in Fig. 17.It can be seen that compared with the adaptive notch method, the proposed ABF method can further reduce the secondary saliency harmonic content in the estimation error greatly.This is because the adaptive notch method is mainly used to suppress the second harmonic.By contrast, the proposed ABF method can suppress the secondary harmonics with more frequencies.Therefore, it can be concluded that the proposed method can effectively decouple the secondary saliency harmonics, which can improve the estimation precision of rotor position and reduce the harmonic loss and torque ripple of the motor drive system.

C. Dynamic Performance
Fig. 18 shows the comparison of the results of the fivephase FIFT-IPM motor based on the traditional algorithm and the ABF secondary harmonic suppression algorithm under variable speed conditions.It can be known that due to the bandwidth limitation of the position observation loop, the estimated rotor position of the traditional algorithm cannot track the actual position quickly at a sudden change of speed.The estimated rotor position error reaches −0.46 and 0.56 rad at the sudden increase and drop speed, respectively.In addition, the large estimated rotor position deviation will cause torque fluctuation and even out-of-step of the motor.To improve the dynamic response performance of sensorless control, the bandwidth dynamic adjustment factor is introduced in this article.When the motor speed changes from 60 to 120 r/min, the estimated rotor position error is −0.3 rad, which is decreased by 34.8%.When the motor Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.speed changes from 120 to 60 r/min, the estimated rotor position error is 0.39 rad, which is decreased by 30.4%.Thus, it can be achieved that the ABF algorithm can significantly improve the estimated performance under the changed speed, can improve the variable-speed operation conditions of EVs, such as frequent start-stop.Moreover, the fluctuation of position estimation error is reduced under different speeds, which verifies the effectiveness of the modified algorithm in suppressing the secondary harmonics.
Fig. 19 shows the comparison results of the five-phase FIFT-IPM motor sensorless control based on conventional HF injection and proposed ABF under different loads.It can be found that when there is a sudden increased load, compared with the conventional method, the position error and the speed oscillation of the proposed method are reduced by 54.6% and 38.9%, respectively.In addition, when there is a sudden decreased load, the position error and the speed oscillation are reduced by 65.3% and 33.5%, respectively.Furthermore, the dynamic adjustment time of the proposed algorithm is shortened under a changed load, and its average position error is also reduced with the increased load.Therefore, with the adoption of the ABF algorithm, the sensorless control performance under the changed load can be significantly improved, which can improve the multiple operating capacities of the EVs.Fig. 20 shows the experimental results of the proposed motor drive system under a dynamic state.The given speed is set as 100 r/min, then changed to a variable frequency sinusoidal signal, and finally set as −100 r/min.The frequency of the sinusoidal signal is set as 0.2 Hz with an increment rate of 0.2 Hz/s.There are two reasons for using this reference signal.It can be observed that the proposed motor drive system can realize four-quadrant operation and can rapidly respond to the dynamic variation of the given speed.In addition, during the four-quadrant operation, the estimated speed can stably and well track the actual speed.With the stable sensorless operation, the effectiveness of the proposed method in fourquadrant operation is verified.Fig. 21 shows the experimental results of the five-phase FIFT-IPM motor based on the traditional method and the proposed method under startup and backward drive.It can be seen that the estimation error of the rotor position is decreased by 35.3% during startup, while that is reduced by 25.5% during the backward drive.In addition, the speed estimation of the proposed method is more stable, and the harmonic content of the position estimation error is less.The effectiveness of the proposed algorithm in startup and backward drive is verified.

V. CONCLUSION
A new active sensorless strategy of a five-phase FIFT-IPM motor drive system under multiple operating conditions has been proposed in this article.With the suppression of the motor saturation effect, including cross-coupling, parameter variations, and secondary saliency, the proposed active sensorless strategy provides merits of improved estimated accuracy of rotor position, reduced harmonic oscillation of rotor position observation, and improved dynamic performance of drive system.The following conclusions are obtained.
1) With the motor design of the enhanced saliency effect, the saliency ratio of the five-phase FIFT-IPM motor has been increased, which could suppress the saturation effect and improve the observation accuracy of the rotor position.By adopting the proposed ABF algorithm, the influence of secondary saliency on position observation could be effectively reduced.Also, the dynamic performance of the sensorless control system could be improved.
2) The proposed active sensorless strategy has improved the sensorless operation capacity of the five-phase motor drive system under multiple working conditions.
The experimental results verified the feasibility and effectiveness of the proposed strategy.3) Furthermore, from the point of view of the motor drive system, this study serves as a reference solving problem of the saturation effect of the sensorless PM motor drive system.

Fig. 4
shows the design concept diagram of the new fivephase FIFT-IPM motor proposed in this article.The 3-D structure diagram of the five-phase FIFT-IPM motor is shown Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.

Fig. 10 .
Fig. 10.Block diagram of the five-phase FIFT-IPM motor drive system based on the new active sensorless strategy.

Fig. 12 .
Fig. 12. Waveforms of the traditional five-phase IPM motor.(a) Speed and estimated speed error.(b) Position and estimated position error.

13 .
Waveforms of the traditional five-phase FIFT-IPM motor with weak saliency.(a) Speed and estimated speed error.(b) Position and estimated position error.

Fig. 16 .
Fig. 16.Experimental waveforms of steady-state performance of the five-phase FIFT-IPM motor.(a) Speed and estimated speed error.(b) Position and estimated position error.
Research on Five-Phase Flux-Intensifying Permanent Magnet Motor Drive System Based on New Active Sensorless Strategy Li Zhang , Member, IEEE, Sai Han, Xiaoyong Zhu , Member, IEEE, Li Quan, Member, IEEE, and Wen-Hua Chen , Fellow, IEEE